Wyatt Alt 6fc6968ccc feat: refresh materialized views
A declared view holds no rows; refresh computes them. It pins one source
version and brings the view to exactly the definition's result at that
version, recording the version as a watermark in the view's schema
metadata. The refresh is incremental when the source changed by nothing but
appends and compactions since the watermark: a transaction-log walk
separates the two, so only genuinely appended fragments are computed --
compaction outputs are already-materialized rows rearranged and cost
nothing, which is what keeps routine background compaction from rebuilding
the view. One subtlety shapes the walk: transaction files record an
Append's fragments with placeholder ids (real ids are assigned at commit),
while a Rewrite's ids are reserved beforehand and real, so appends are
derived as new-at-head minus rewrite outputs rather than read from the log.
A fragment-signature check scoped to the columns the view reads is the
fallback for deltas the walk cannot classify, and passes changes to
unrelated columns.

Deletes and updates reconcile incrementally too: the lance delta reports
the row ids the range deleted, the view evicts exactly those provenance
ids, and updated rows are named by their row-version columns and
recomputed. Past a fixed cap of staged ids -- or on a Legacy-storage
source, which cannot serve the row-version columns -- refresh falls back
to a rebuild, as it does for a vacuumed watermark version or an append a
later compaction swallowed. A rebuild of an indexed view stages the new
fragments uncommitted and commits one Update swapping out every old
fragment, so index definitions are never absent and readers never observe
an empty view; unindexed rebuilds overwrite, with the watermark riding the
same commit. Refresh also accepts a pinned source version, and a row limit
counts already-held rows.

Concurrent refreshes of one view serialize at commit: each carries the
same sentinel row id in its inserted-rows filter, so the loser's commit
conflicts and lands nothing rather than double-applying. The remaining
bound, stated in the module docs: on the append path the watermark moves
in a follow-up commit, so a crash between the two re-appends those rows on
the next refresh.
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LanceDB Cloud Public Beta

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LanceDB

The Multimodal AI Lakehouse

How to Install Detailed DocumentationTutorials and RecipesContributors

The ultimate multimodal data platform for AI/ML applications.

LanceDB is designed for fast, scalable, and production-ready vector search. It is built on top of the Lance columnar format. You can store, index, and search over petabytes of multimodal data and vectors with ease. LanceDB is a central location where developers can build, train and analyze their AI workloads.


Demo: Multimodal Search by Keyword, Vector or with SQL

LanceDB Multimodal Search

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Key Features:

  • Fast Vector Search: Search billions of vectors in milliseconds with state-of-the-art indexing.
  • Comprehensive Search: Support for vector similarity search, full-text search and SQL.
  • Multimodal Support: Store, query and filter vectors, metadata and multimodal data (text, images, videos, point clouds, and more).
  • Advanced Features: Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure. GPU support in building vector index.

Products:

  • Open Source & Local: 100% open source, runs locally or in your cloud. No vendor lock-in.
  • Cloud and Enterprise: Production-scale vector search with no servers to manage. Complete data sovereignty and security.

Ecosystem:

  • Columnar Storage: Built on the Lance columnar format for efficient storage and analytics.
  • Seamless Integration: Python, Node.js, Rust, and REST APIs for easy integration. Native Python and Javascript/Typescript support.
  • Rich Ecosystem: Integrations with LangChain 🦜🔗, LlamaIndex 🦙, Apache-Arrow, Pandas, Polars, DuckDB and more on the way.

How to Install:

Follow the Quickstart doc to set up LanceDB locally.

API & SDK: We also support Python, Typescript and Rust SDKs

Interface Documentation
Python SDK https://lancedb.github.io/lancedb/python/python/
Typescript SDK https://lancedb.github.io/lancedb/js/globals/
Rust SDK https://docs.rs/lancedb/latest/lancedb/index.html
REST API https://docs.lancedb.com/api-reference/rest

Join Us and Contribute

We welcome contributions from everyone! Whether you're a developer, researcher, or just someone who wants to help out.

If you have any suggestions or feature requests, please feel free to open an issue on GitHub or discuss it on our Discord server.

Check out the GitHub Issues if you would like to work on the features that are planned for the future. If you have any suggestions or feature requests, please feel free to open an issue on GitHub.

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